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acge_text_embedding

Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
mteb
feature-extraction
Eval Results
text-embeddings-inference
Inference Endpoints
Model card Files Community
16
acge_text_embedding
File size: 1,456 Bytes 
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{
  "dataset_revision": "66e76a618a34d6d565d5538088562851e6daa7ec",
  "mteb_dataset_name": "Ocnli",
  "mteb_version": "1.1.2",
  "validation": {
    "cos_sim": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.5931570529937744,
      "ap": 0.8516141108141811,
      "f1": 0.8297771455666192,
      "f1_threshold": 0.5646798610687256,
      "precision": 0.7530120481927711,
      "recall": 0.9239704329461457
    },
    "dot": {
      "accuracy": 0.8105035192203573,
      "accuracy_threshold": 0.5924628973007202,
      "ap": 0.8513568069803823,
      "f1": 0.8304038004750595,
      "f1_threshold": 0.5658385157585144,
      "precision": 0.7547495682210709,
      "recall": 0.9229144667370645
    },
    "euclidean": {
      "accuracy": 0.8110449377368706,
      "accuracy_threshold": 0.8982482552528381,
      "ap": 0.8516341835376644,
      "f1": 0.8296860133206471,
      "f1_threshold": 0.9301300048828125,
      "precision": 0.754978354978355,
      "recall": 0.9208025343189018
    },
    "evaluation_time": 2.98,
    "manhattan": {
      "accuracy": 0.8115863562533838,
      "accuracy_threshold": 30.367427825927734,
      "ap": 0.8513388548299352,
      "f1": 0.8291048348492102,
      "f1_threshold": 31.26837158203125,
      "precision": 0.7583187390542907,
      "recall": 0.914466737064414
    },
    "max": {
      "accuracy": 0.8115863562533838,
      "ap": 0.8516341835376644,
      "f1": 0.8304038004750595
    }
  }
}